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» Kernels for Multi--task Learning
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ADCM
2008
136views more  ADCM 2008»
13 years 8 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou
AUTOMATICA
2006
103views more  AUTOMATICA 2006»
13 years 8 months ago
A universal iterative learning stabilizer for a class of MIMO systems
Design of iterative learning control (ILC) often requires some prior knowledge about a system's control matrix. In some applications, such as uncalibrated visual servoing, th...
Ping Jiang, Huadong Chen, Leon C. A. Bamforth
CORR
2010
Springer
123views Education» more  CORR 2010»
13 years 6 months ago
Feature Construction for Relational Sequence Learning
Abstract. We tackle the problem of multi-class relational sequence learning using relevant patterns discovered from a set of labelled sequences. To deal with this problem, firstly...
Nicola Di Mauro, Teresa Maria Altomare Basile, Ste...
ACCV
2010
Springer
13 years 3 months ago
Unsupervised Selective Transfer Learning for Object Recognition
Abstract. We propose a novel unsupervised transfer learning framework that utilises unlabelled auxiliary data to quantify and select the most relevant transferrable knowledge for r...
Wei-Shi Zheng, Shaogang Gong, Tao Xiang
JMLR
2010
103views more  JMLR 2010»
13 years 2 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider